summary.gls {nlme} | R Documentation |

## Summarize a gls Object

### Description

Additional information about the linear model fit represented
by `object`

is extracted and included as components of
`object`

. The returned object is suitable for printing with the
`print.summary.gls`

method.

### Usage

## S3 method for class 'gls':
summary(object, verbose, ...)

### Arguments

`object` |
an object inheriting from class `gls` , representing
a generalized least squares fitted linear model. |

`verbose` |
an optional logical value used to control the amount of
output in the `print.summary.gls` method. Defaults to
`FALSE` . |

`...` |
some methods for this generic require additional
arguments. None are used in this method. |

### Value

an object inheriting from class `summary.gls`

with all components
included in `object`

(see `glsObject`

for a full
description of the components) plus the following components:

`corBeta` |
approximate correlation matrix for the coefficients
estimates |

`tTable` |
a data frame with columns `Value` ,
`Std. Error` , `t-value` , and `p-value` representing
respectively the coefficients estimates, their approximate standard
errors, the ratios between the estimates and their standard errors,
and the associated p-value under a *t* approximation. Rows
correspond to the different coefficients. |

`residuals` |
if more than five observations are used in the
`gls` fit, a vector with the minimum, first quartile, median, third
quartile, and maximum of the residuals distribution; else the
residuals. |

`AIC` |
the Akaike Information Criterion corresponding to
`object` . |

`BIC` |
the Bayesian Information Criterion corresponding to
`object` . |

### Author(s)

Jose Pinheiro Jose.Pinheiro@pharma.novartis.com and Douglas Bates bates@stat.wisc.edu

### See Also

`gls`

, `AIC`

, `BIC`

,
`print.summary.gls`

### Examples

fm1 <- gls(follicles ~ sin(2*pi*Time) + cos(2*pi*Time), Ovary,
correlation = corAR1(form = ~ 1 | Mare))
summary(fm1)

[Package

*nlme* version 3.1-66

Index]